Molecular correlates of trait anxiety [Elektronische Ressource] : expanding biomarker discovery from protein expression to turnover / Yaoyang Zhang

Dissertation zur Erlangung des Doktorgrades
der Fakultät für Biologie
der Ludwig-Maximilians-Universität München


Molecular correlates of trait anxiety: expanding
biomarker discovery from protein expression to
turnover




Yaoyang Zhang
from
Henan, PR China
July, 2010


















Erstgutachter: Prof. Dr. Rainer Landgraf
Zweitgutachter: Prof. Dr. Gisela Grupe
Tag der mündlichen Prüfung: 02.12.2010
i Contents
Contents
1 Abstract .................................................................................................... 1
2 Introduction ............................. 3
2.1 Anxiety and depression ................................................................................. 3
2.1.1 Anxiety and depressive disorders ........................... 3
2.1.2 Anxiety mouse model ............. 4
2.2 Proteomics .................................................................................................... 6
2.2.1 Mass spectrometry ................. 7
2.2.2 Protein identification by mass spectrometry ....... 10
2.2.3 2-DE based proteomics ......................................................................... 11
2.2.4 Shotgun proteomics ............. 12
2.2.5 Quantitative proteomics ....... 12
2.3 Metabolomics .............................................................................................. 20
2.4 Systems biology ........................... 21
2.5 Biomarkers .................................................................................................. 22
3 Proteomic and metabolomic brain and plasma profiling of a trait anxiety
mouse model ...................................................................................................... 25
3.1 Introduction . 25
3.2 Material and methods ................................................................................. 26
3.2.1 Materials ............................... 26
3.2.2 Animal experiments .............. 26
3.2.3 Quantitative proteomics ....................................................................... 28
3.2.4 Corticosterone assay ............ 34
3.2.5 GO and KEGG analysis .......... 34
3.2.6 Western blot analysis ........................................................................... 35
3.2.7 Metabolomics ....................... 35
3.2.8 Pathway analysis ................................................................................... 38
iii Contents
3.3 Results ......................................................................................................... 39
3.3.1 Animal experiments ............. 39
3.3.2 Quantitative proteomics ...... 43
3.3.3 Corticosterone assay ............................................................................ 53
3.3.4 Western blot validation ........ 53
3.3.5 Metabolomics ...................................................................................... 68
3.3.6 Pathway analysis .................. 74
3.4 Discussion ................................................................................................... 87
3.4.1 Isotope effect ....................... 87
3.4.2 Pathobiology of the anxiety phenotype .............................................. 89
4 Technology development ........................................ 97
154.1 A mass spectrometry data search method for improved N-labeled protein
identification ......................................................................... 97
4.1.1 Introduction ......................................................................................... 97
4.1.2 Material and methods ......................................... 98
4.1.3 Results ................................................................ 101
4.1.4 Discussion........................................................... 103
4.2 Proteome scale turnover analysis in living animals using stable isotope
metabolic labeling .............................................................................................. 105
4.2.1 Introduction ....................... 105
4.2.2 Material and methods ....................................................................... 107
4.2.3 Results ................................ 114
4.2.4 Discussion........................................................... 125
5 Perspectives .......................................................... 131
6 References ............................................................ 133
7 Supplementary tables ........................................................................... 153
8 Abbreviations........................ 163
9 Acknowledgements ............................................................................... 165
10 Curriculum Vitae ................... 167
iv Abstract
1 Abstract
Depression and anxiety disorders affect a great number of people in the world. Although
remarkable efforts have been devoted to understanding the clinical and biological basis of
these disorders, progress has been relatively slow. Furthermore, no laboratory test
currently is available for diagnosis of anxiety and depression. These disorders are mainly
diagnosed empirically on the basis of a doctor’s personal observations and experiences.
Hence, discovery of biomarkers for these psychiatric disorders deserves much scientific
attention.
The animal models investigated in the present study represent high, low, and normal
anxiety-like phenotypes (HAB, LAB, NAB) and were established by selective inbreeding. To
compare the protein expression levels between different animal lines, living animals were
15metabolically labeled with the N stable isotope and then investigated by quantitative
mass spectrometry. In addition, metabolomic studies were performed to shed light on
pathways affected in the trait anxiety mouse model. A number of proteins and metabolites
were found to be significantly altered in their expression levels between the three mouse
lines. Both protein and metabolite information was used for in silico network analysis to
find pathways pertinent to the pathobiology of anxiety disorders.
Another focus of this thesis was the development of new methodologies for the metabolic
labeling approach. This includes improved identification of labeled proteins and the
analysis of protein turnover. The latter represents another important aspect in the field of
proteomics and adds a dynamic dimension to the field. The method allows the detection
of protein expression alterations at a much earlier stage. The newly developed ProTurnyer
(Protein Turnover Analyzer) algorithm is able to calculate in a high throughput manner
turnover for individual proteins.
1 Introduction
2 Introduction
2.1 Anxiety and depression
2.1.1 Anxiety and depressive disorders
Up to 20% of the world’s population suffers from depression or anxiety disorders (Kessler
et al., 1994). According to data published by the World Health Organization (WHO),
currently depressive disorders are the fourth leading cause of disability in the world and
are likely to rise to the second position by 2020. The symptoms of depression and anxiety,
such as sadness, hopelessness, feeling of being worthless, diminished interest, anxiety,
worry, fear etc., exist in almost everyone’s daily life, but in people without mental illness
these feelings usually appear to be reasonable and disappear within a couple of hours or
days. However, these symptoms are much more persistent and excessive in a person with
depression or anxiety or both. Thus, these disorders can interfere severely with patients’
lives, the lives of their families, and society in general.
Although remarkable efforts have been devoted to understanding the clinical and
biological basis of depression and anxiety, progress has been relatively slow. Epidemiologic
studies have demonstrated that heredity factors can contribute roughly 40%-50% to the
risk for depression (Fava and Kendler, 2000). In twin studies, 15%-20% heritability was
observed for anxiety disorders (Hettema et al., 2001). One promising hypothesis of
depression is based on dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and
the relevant components, such as corticotrophin-releasing factor (CRF),
adrenocorticotropin (ACTH) and glucocorticoid. Hyperactivity of the HPA axis is observed
in approximately half of depressed individuals. A number of factors have been studied and
found to be highly relevant for anxiety. For instance, inactivation of the gamma-amino
butyric acid (GABA) synthesis enzyme or its receptors resulted in increased anxiety-like
behavior (Kash et al., 1999; Low et al., 2000). Similarly, inactivation of the 5-HT1A receptor
also increased anxiety-like behavior in mice (Heisler et al., 1998; Parks et al., 1998; Ramboz
et al., 1998). In addition, monoamine oxidase A (MAO-A) (Cases et al., 1995), and CRF and
its receptors (Bale et al., 2002; Smith et al., 1998a) have been found to regulate anxiety.
Comorbidity is a quite common occurrence in psychiatric disorders. Data have shown that
during one year, almost 50% of psychiatric patients have two or more syndromes (Kessler
3 Anxiety and depression
et al., 20